The International Network for Optimal Resistance Monitoring (INFORM) global surveillance program collected clinical isolates of
(
= 7,665) and
(
= 1,794) from 26 medical centers in six Latin ...American countries from 2012 to 2015. The
activity of ceftazidime-avibactam and comparators was determined for the isolates using the Clinical and Laboratory Standards Institute (CLSI) reference broth microdilution method.
were highly susceptible (99.7%) to ceftazidime-avibactam, including 99.9% of metallo-β-lactamase (MBL)-negative isolates; 87.4% of all
isolates and 92.8% of MBL-negative isolates were susceptible to ceftazidime-avibactam. Susceptibility to ceftazidime-avibactam ranged from 99.4% to 100% for
and from 79.1% to 94.7% for
when isolates were analyzed by country of origin. Ceftazidime-avibactam inhibited 99.6% to 100% of
isolates that carried serine β-lactamases, including extended-spectrum β-lactamases (ESBLs), AmpC cephalosporinases, and carbapenemases (KPC and OXA-48-like) as well as 99.7%, 99.6%, 99.5%, and 99.2% of MBL-negative isolates demonstrating ceftazidime-nonsusceptible, multidrug-resistant (MDR), meropenem-nonsusceptible, and colistin-resistant phenotypes, respectively. Among carbapenem-nonsusceptible isolates of
(
= 750), 14.7% carried MBLs with or without additional acquired serine β-lactamases, while in the majority of isolates (70.0%), no acquired β-lactamase was identified. Ceftazidime-avibactam inhibited 89.5% of carbapenem-nonsusceptible
isolates in which no acquired β-lactamase was detected. Overall, clinical isolates of
collected in Latin America from 2012 to 2015 were highly susceptible to ceftazidime-avibactam, including isolates that exhibited resistance to ceftazidime, meropenem, colistin, or an MDR phenotype. Country-specific variations were noted in the susceptibility of
isolates to ceftazidime-avibactam.
The Antimicrobial Testing Leadership and Surveillance (ATLAS) global surveillance program collected clinical isolates of Enterobacterales (n = 8416) and Pseudomonas aeruginosa (n = 2521) from 41 ...medical centers in 10 Latin American countries from 2017 to 2019. In vitro activities of ceftazidime-avibactam and comparators were determined using the Clinical and Laboratory Standards Institute (CLSI) broth microdilution method. Overall, 98.1% of Enterobacterales and 86.9% of P. aeruginosa isolates were susceptible to ceftazidime-avibactam. When isolates were analyzed by country of origin, susceptibility to ceftazidime-avibactam for Enterobacterales ranged from 97.8% to 100% for nine of 10 countries (except Guatemala, 86.3% susceptible) and from 75.9% to 98.4% for P. aeruginosa in all 10 countries. For Enterobacterales, 100% of AmpC-positive, ESBL- and AmpC-positive, GES-type carbapenemase-positive, and OXA-48-like-positive isolates were ceftazidime-avibactam-susceptible as were 99.8%, 91.8%, and 74.7% of ESBL-positive, multidrug-resistant (MDR), and meropenem-nonsusceptible isolates. Among meropenem-nonsusceptible isolates of Enterobacterales, 24.4% (139/570) carried a metallo-β-lactamase (MBL); 83.3% of the remaining meropenem-nonsusceptible isolates carried another class of carbapenemase and 99.4% of those isolates were ceftazidime-avibactam-susceptible. Among meropenem-non-susceptible isolates of P. aeruginosa (n = 835), 25.6% carried MBLs; no acquired β-lactamase was identified in the majority of isolates (64.8%; 87.2% of those isolates were ceftazidime-avibactam-susceptible). Overall, clinical isolates of Enterobacterales collected in Latin America from 2017 to 2019 were highly susceptible to ceftazidime-avibactam, including isolates carrying ESBLs, AmpCs, and KPCs. Country-specific variation in susceptibility to ceftazidime-avibactam was more common among isolates of P. aeruginosa than Enterobacterales. The frequency of MBL-producers among Enterobacterales from Latin America was low (1.7% of all isolates; 146/8,416), but higher than reported in previous surveillance studies.
I propose a very simple model of strategic communication. The motivation is to help explain widespread persistent disagreement about objective facts. In the model, there is a message sender and a ...receiver, and two possible states of the world, left or right. The sender is one of three types: honest, or a leftist or rightist "ideologue." The honest type observes a private signal in {0, 1, . . . ,𝑁}, with higher values implying stronger support for the right state, and reports the observed value truthfully. Ideologues strategically choose any message from this set to maximize the receiver's belief in their preferred state, ignoring any private information they may have. I show that a small presence of ideologues can have a large effect on communication: while we might expect ideologues to just send extreme messages, in most equilibria ideologues use "strategic understatement," and in many cases actually mix over all non-neutral (non-𝑁/2) messages to mimic honest types and gain credibility. This distorts the interpretation of these messages such that all messages on a side of the spectrum (above or below 𝑁/2) have the same effect on receiver beliefs. This coarsened communication is less informative than even the weakest non-neutral messages in the absence of ideologues. I show by example how ideologues can cause large delays in the time required for receiver beliefs to converge to truth.
Zika virus (ZIKV) is a flavivirus primarily transmitted by
Aedes
species mosquitoes, first discovered in Africa in 1947, that disseminated through Southeast Asia and the Pacific Islands in the 2000s. ...The first ZIKV infections in the Americas were identified in 2014, and infections exploded through populations in Brazil and other countries in 2015/16. ZIKV infection during pregnancy can cause severe brain and eye defects in offspring, and infection in adults has been associated with higher risks of Guillain-Barré syndrome. We initiated a study to describe the natural history of Zika (the disease) and the immune response to infection, for which some results have been reported. In this paper, we identify ZIKV-specific CD4+ and CD8+ T cell epitopes that induce responses during infection. Two screening approaches were utilized: an untargeted approach with overlapping peptide arrays spanning the entire viral genome, and a targeted approach utilizing peptides predicted to bind human MHC molecules. Immunoinformatic tools were used to identify conserved MHC class I supertype binders and promiscuous class II binding peptide clusters predicted to bind 9 common class II alleles. T cell responses were evaluated in overnight IFN-γ ELISPOT assays. We found that MHC supertype binding predictions outperformed the bulk overlapping peptide approach. Diverse CD4+ T cell responses were observed in most ZIKV-infected participants, while responses to CD8+ T cell epitopes were more limited. Most individuals developed a robust T cell response against epitopes restricted to a single MHC class I supertype and only a single or few CD8+ T cell epitopes overall, suggesting a strong immunodominance phenomenon. Noteworthy is that many epitopes were commonly immunodominant across persons expressing the same class I supertype. Nearly all of the identified epitopes are unique to ZIKV and are not present in Dengue viruses. Collectively, we identified 31 immunogenic peptides restricted by the 6 major class I supertypes and 27 promiscuous class II epitopes. These sequences are highly relevant for design of T cell-targeted ZIKV vaccines and monitoring T cell responses to Zika virus infection and vaccination.
Pulling starters Finigan, Duncan; Mills, Brian M.; Stone, Daniel F.
Journal of behavioral and experimental economics,
12/2020, Letnik:
89
Journal Article
Recenzirano
•We study the fundamental decision in baseball of when to pull the starting pitcher.•We show theoretically that runs should decline at the time the starter is pulled.•Empirically this occurs, and win ...probability is unaffected by pulling the starter.•Both results are consistent with win maximization by managers.•We also fail to find biases caused by recent events or other game factors.
We theoretically and empirically study a fundamental strategic decision in baseball: when to make the “call to the bullpen” and pull th=e starting pitcher. The limited previous literature on this topic found that pulling starters tends to reduce runs allowed in the current inning. We show with a simple model that this result is consistent with win maximization, and does not necessarily imply that starters should typically be pulled sooner. We then use detailed pitch-level data from the 2008–2017 seasons to estimate the effects of pulling the starter on both runs allowed in the current inning and on win probability. We argue that whether or not the starter is pulled is plausibly “as good as random” conditional on the large set of included covariates, but acknowledge the lack of true randomization. We find that the estimated effect of pulling the starter on runs allowed in the current inning is indeed negative, but the effect on win probability is a precise zero. We examine a variety of game situations and recent events, and find only scattered and limited evidence of biases, but note that statistical power is limited for these analyses. We interpret the results to imply that, at least on average, decisions for when to pull starters were approximately Bayesian-optimal in between plate appearances due to a period of institutional learning that occurred over decades. However, starters were very rarely pulled within-plate appearances, so we cannot analyze the optimality of these decisions.
This paper empirically investigates three hypotheses regarding biases of National Basketball Association referees. Identification of basketball referee bias is typically difficult as changes in ...observed statistics may be caused by either changes in referee bias or player behavior. We identify bias by exploiting the fact that referees have varying degrees of discretion over different types of a particular statistic‐turnovers. This allows us to conduct a treatment and control‐style analysis, using the less discretionary turnovers as the player behavior control. The results provide evidence that referees favor home teams, teams losing during games, and teams losing in playoff series. All three biases are likely to increase consumer demand.
Media and gridlock Stone, Daniel F.
Journal of public economics,
05/2013, Letnik:
101
Journal Article
Recenzirano
I develop a model of the relation between the media environment and political obstructionism. I show that when voters are less informed by media, obstructionism becomes a more effective political ...signal for the minority party. The model thus implies that media change can cause gridlock via signaling; by contrast, the previous literature on causes of gridlock focuses on polarization and other factors. The model also makes several auxiliary predictions consistent with recent trends in U.S. politics.
•I show that less informative media can cause strategic political obstructionism.•This theory for gridlock is novel, as previous literature focuses on polarization.•I argue gridlock and other U.S. political trends are caused partly by media change.•In particular, gridlock may worsen political reputations, which then exacerbate gridlock.
Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram‐based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). ...Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen‐detected cases and 1197 matched controls; and 354 younger‐diagnosis cases and 944 controls frequency‐matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually‐ and frequency‐matched studies, respectively. We estimated measure‐specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen‐detected and younger‐diagnosis cancer risks, the best fitting models (OPERAs 95% confidence intervals) involved: Cumulus (1.81 1.41‐2.31) and Cirrus (1.72 1.38‐2.14); Cirrus (1.49 1.32‐1.67) and Cirrocumulus (1.16 1.03 to 1.31); and Cirrus (1.70 1.48 to 1.94) and Cirrocumulus (1.46 1.27‐1.68), respectively. The AUCs were: 0.73 0.68‐0.77, 0.63 0.60‐0.66, and 0.72 0.69‐0.75, respectively. Combined, our new mammogram‐based measures have twice the risk gradient for screen‐detected and younger‐diagnosis breast cancer (P ≤ 10−12), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk‐based personalised breast screening.
What's new?
Mammographic density, or the area of the mammogram which appears white or bright, has well‐established associations with breast cancer risk. The authors call this Cumulus due to the computer‐assisted technique for measuring that density. Here, the authors introduce two novel measurement techniques, Cirrus and Cirrocumulus, for extracting risk information from mammograms. Cirrocumulus is based on image brightness and Cirrus is based on texture. When combined, these measures substantially improve risk prediction beyond that of Cumulus. In addition, the new risk measures outperformed the recently published polygenic risk score. By obtaining more information from mammograms, these tools could improve personalized risk recommendations for screening.
Ferraro and Taylor (2005) and Potter and Sanders (2012) have sparked a debate about the definition of opportunity cost (OC). This is, of course, ostensibly a very basic term, but Ferraro and Taylor ...said that most economists do not readily know its correct definition, and Potter and Sanders argued that this can be explained by the fact that there is no standard definition. In Stone (2015), the author of this article tried to contribute to this debate by pointing out that the term OC is commonly used, in both textbooks and the popular press, in two distinct ways: sometimes to refer to just an implicit cost (e.g., "the opportunity cost of lost earnings from attending college") and sometimes to refer to a total economic cost (lost earnings plus tuition, etc.). Stone then suggested using the terms implicit and explicit cost when discussing basic choice problems (e.g., the Clapton/Dylan example of Ferraro and Taylor) at the start of economics classes and books, to make the correct definition of economic cost unambiguous and the logic of analysis more clear. In summary, Stone states that re-reading Parkin's paper carefully and writing this piece have made him see that there are important differences between the quantity and value versions of OC and that for either version there are hidden "costs" of which one should be aware. Stone concludes by saying that however this discussion proceeds, he hopes that it will be a case in point of how open-minded scholars can learn from one another and come to an enlightened consensus.
Abstract
Background
The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in ...relatives, so familial aspects of risk (genetic and non-genetic) must be considered.
Development
We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID’s building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher’s classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors.
Application
For female breast cancer, VALID quantified how much variance in risk is explained—at different ages—by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors.
Conclusion
VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.
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